Details:

Alternative Title:
J Biomech
Personal Author:
Merrill, Zachary ; Perera, Subashan ; Cham, Rakié
Merrill, Zachary ; Perera, Subashan ; Cham, Rakié Less -
Description:
Body segment parameters such as segment mass, center of mass, and radius of gyration are used as inputs in static and dynamic ergonomic and biomechanical models used to predict joint and muscle forces, and to assess risks of musculoskeletal injury. Previous work has predicted body segment parameters (BSPs) in the general population using age and obesity levels as statistical predictors (Merrill et al., 2017). Estimated errors in the prediction of BSPs can be as large as 40%, depending on age, and the prediction method employed (Durkin and Dowling, 2003). Thus, more accurate and representative segment parameter inputs are required for attempting to predict modeling outputs such as joint contact forces, muscle forces, and injury risk in individuals. This study aims to provide statistical models for predicting torso, thigh, shank, upper arm, and forearm segment parameters in working adults using whole body dual energy x-ray absorptiometry (DXA) scan data along with a set of anthropometric measurements. The statistical models were developed on a training data set, and independently validated on a separate test data set. The predicted BSPs in validation data were, on average, within 5% of the actual in vivo DXA-based BSPs, while previously developed predictions (de Leva, 1996) had average errors of up to 60%, indicating that the new models greatly increase the accuracy in predicting segment parameters. These final developed models can be used for calculating representative BSPs in individuals for use in modeling applications dependent on these parameters.
Subject:
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Absorptiometry, Photon Adult Age Aged Anthropometry Arm Article Body Mass Index Body Segment Parameters Female Forearm Humans Leg Male Middle Aged Models, Statistical Obesity Regression Analysis Thigh Torso Young Adult Anthropometry
Source:
J Biomech. 96:109349
Pubmed ID:
31615644
Pubmed Central ID:
PMC6905426
Document Type:
Journal Article
Funding:
R01 OH010106/OH/NIOSH CDC HHS/United States
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:62d00af8a485c8d712455715b8a7be107a602c7ae232f465f1b08191205e4d3c
Download URL:
https://stacks.cdc.gov/view/cdc/83569/cdc_83569_DS1.pdf
File Type:

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